Transforming Small Businesses 2025

Framework for prioritizing implementation of AI use cases FIGURE 6 Backburner Deprioritize, reassess periodically in case market or tech evolveQuick wins Good for building AI capabilitiesIdeal AI pilots Use cases for early adoption, scale once proven successfulInvestable bets Invest in R&D and infrastructure to improve feasibility, gradual pilotsMultiple use cases for AI in SMEs exist Prioritize high-impact and feasibility use cases to accelerate adoption High HighMedium MediumLow Low FeasibilityImpact Source: World Economic ForumPrioritizing AI use cases for Indian SMEs AI has the potential to transform many aspects of SME operations, but not all use cases are equally viable for immediate implementation. To ensure a structured approach to AI adoption in SMEs, each AI use case should be assessed on two parameters – impact delivery and feasibility of implementation – which can be further broken down into a few sub-parameters: 1. Impact – the potential value created in the business as a direct result of use case implementation: –Business value: Tangible benefits such as revenue growth or cost reduction –Strategic alignment: Alignment of use case with the long-term goals of the business or with strategically important areas –People impact: The number of people in the workforce who will be affected by use case implementation2. Feasibility of implementation – ease with which the use case can be implemented in the organization’s current context: –Data readiness: Availability of relevant structured data for use case implementation –Operational readiness: Existing infrastructure and workforce capability to implement AI solution –Cost to deploy: Investment required for successful implementation of use case Given the limited resources available to SMEs, AI use cases must be implemented in a phased manner. Initially, SMEs should focus on use cases that have a high impact on the business while being relatively easy to implement. To do this, each use case must be evaluated against the parameters listed above to arrive at scores for impact and feasibility. The use cases can then be prioritized as illustrated in Figure 6. Initially, SMEs should focus on use cases that have a high impact on the business while being relatively easy to implement. While this framework addresses how individual SMEs can prioritize AI use cases for implementation, it can help determine use case prioritization at a cluster level as well. When this happens, instead of looking at the impact and feasibility with respect to an individual organization, the parameters can be scored based on the cluster average. Transforming Small Businesses: An AI Playbook for India’s SMEs 26